EDP Sciences logo
Search
Menu
All issues Volume 63 / No 6 (September 2006) Ann. For. Sci., 63 6 (2006) 579-595 References
Open Access
Issue
Ann. For. Sci.
Volume 63, Number 6, September 2006
Impacts of drought and heat on forests
Synthesis of available knowledge, with emphasis on the 2003 event in Europe
Page(s) 579 - 595
DOI https://doi.org/10.1051/forest:2006045
Published online 14 September 2006
References of  Ann. For. Sci. 63 (2006) 579-595
  1. Anonymous, Remote sensing applications for forest health status assessment. European Union Scheme on the protection of forests against atmospheric pollution, 2nd ed., Office of Publications of European Communities, Luxembourg, 2000, 216 p.
  2. Anonymous, SEMEFOR, Satellite based environmental monitoring of European forests. Project report. European Commission, Research Directorate-General Science, Research and development, Environment and climate program 1994-1998, Contract ENV4-CT97-0398, ISBN92-894-0851-0, 2002, 103 p.
  3. Anselmi S., Chiesi M., Giannini M., Manes F., Maselli F., Estimation of Mediterranean forest transpiration and photosynthesis through the use of an ecosystem simulation model driven by remotely sensed data, Glob. Ecol. Biogeogr. 13 (2004) 371-380 [CrossRef].
  4. Archaux F., Wolters V., Impact of summer drought on forest biodiversity, Ann. For. Sci. 63 (2006) 643-650.
  5. Bannari A., Morin D., Bonn F., Huete A.R., A review of vegetation indices, Remote Sens. Rev. 13 (1995) 20-95.
  6. Bazire P., Guyon D., Jolly A., Riom J., Lallemand C., Legendre G., Étude par Télédétection spatiale du dépérissement des forêts vosgiennes, in: Colloque Intern. SPOT 1, Utilisation des images, bilan, résultats, Paris, 23-27 novembre 1987, pp. 997-1011.
  7. Bochenek Z., Ciolkosz A., Iracka M., Deterioration of forests in the Sudety Mountains, Poland, detected on satellite images, Environ. Pollut. 98 (1997) 375-379 [CrossRef].
  8. Bourgeau-Chavez L.L., Kasischke E.S., Brunzell S., Mudd J.P., Tukman M., Mapping fire scars in global boreal forests using imaging radar data, Int. J. Remote Sens. 23-20 (2002) 4211-4234 [CrossRef].
  9. Bowman W.D., The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves, Remote Sens, Environ. 30 (1990) 249-255.
  10. Bowyer P., Danson F.M., Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level, Remote Sens. Environ. 92 (2004) 297-308 [CrossRef].
  11. Bréda N., Duchemin B., Granier A., Lagouarde J.P., Ogée J., Relationships between surface temperature and fluxes: a comparative analysis for temperate deciduous and coniferous forests, in: Proc. International conference, ALPS-CNES, Remote sensing and vegetation productivity, Méribel, 18-22 January 1999, P-15, 4 p.
  12. Bréda N., Huc R., Granier A., Dreyer E., Forest trees and stands under drought: a review of ecophysiological responses, adaptation processes and long-term consequences, Ann. For. Sci. 63 (2006) 623-642.
  13. Brown L., Chen J.M., Leblanc S.G., Cihlar J., A Shortwave Infrared Modification to the Simple Ratio for LAI Retrieval in Boreal Forests: An Image and Model Analysis, Remote Sens. Environ. 71 (2000) 16-25 [CrossRef].
  14. Calvet J.-C., Noilhan J., Roujean J.-L., Bessemoulin P., Cabelguenne M., Olioso A., Wigneron J.P., An interactive vegetation SVAT model tested against data from six contrasting sites, Agric. For. Meteorol. 92 (1998) 73-95 [CrossRef].
  15. Cardot H., Faivre R., Maisongrande P., Random effects varying-time regression models: applications in remote sensing, in: Antoch J. (Ed.), Compstat 2004, Physica-Verlag, 2004, pp. 777-784.
  16. Ceccato P., Flasse S., Tarantola S., Jacquemoud S., Grégoire J.M., Detecting vegetation leaf water content using reflectance in the optical domain, Remote Sens. Environ. 77 (2001) 22-33 [CrossRef].
  17. CEOS, Committee on Earth observation satellites, http://www.ceos.org/pdfs/CEOS_brochure_Sep04E.pdf. 2004, 12 p.
  18. Ciais P., Reichstein M., Viovy N., Granier A., Ogée J., Allard V., Aubinet M., Buchmann N., Bernhofer C., Carrara A., Chevallier F., De Noblet N., Friend A.D., Friedlingstein P., Grunwald T., Heinesch B., Keronen P., Knohl A., Krinner G., Loustau D., Manca G., Matteucci G., Miglietta F., Ourcival J.M., Papale D., Pilegaard K., Rambal S., Seufert G., Soussana J.F., Sanz M.J., Schulze E.D., Vesala T., Valentini R., Europe-wide reduction in primary productivity caused by the heat and drought in 2003, Nature 437-7058 (2005) 529-533 [CrossRef].
  19. Ciesla W.M., Dull C.W., Acciavatti R.E., Interpretation of SPOT-1 color composites for mapping defoliation of hardwood forests by gypsy moth, Photogramm. Eng. Remote Sens. 55 (1989) 1465-1470.
  20. Coret L., Maisongrande P., Boone A., Lobo A., Dedieu G., Gouaux P., Assessing the impacts of the 2003 hot and dry spell with SPOT HRVIR images time series over south-western France, Int. J. Remote Sens. 26 (2005) 2461-2469 [CrossRef].
  21. Couteron P., Pelissier R., Nicolini E.A., Paget D., Predicting tropical forest stand structure parameters from Fourier transform of very high-resolution remotely sensed canopy images, J. Appl. Ecol. 42 (2005) 1121-1128.
  22. Dennison P.E., Roberts D.A., Thorgusen S.R., Regelbrugge J.C., Weise D., Lee C., Modeling seasonal changes in live fuel moisture and equivalent water thickness using a cumulative water balance index, Remote Sens. Environ. 88 (2003) 442-452 [CrossRef].
  23. Dennison P.E., Roberts D.A., Examining seasonal changes in canopy moisture and vegetation recovery from wildfire using AVIRIS time series data, in: AVIRIS Earth Science and Applications Workshop, March 31-April 2, 2004, Pasadena, California.
  24. Deshayes M., Stach N., Cartographie par télédétection des défoliations des chênes par le bombyx disparate dans le centre-ouest. Rapport final, Convention DERF N° 01.40.14/98, 1999, 29 p., 2 cartes hors-texte.
  25. Deshayes M., Stach N., Malphettes J.B., Utilisation des images satellitales pour l'observation des défoliations dues au bombyx disparate en forêt de Haguenau, Les Cahiers du DSF 1 (1998) 87-89.
  26. Desprez-Loustau M.L., Marcais B., Nageleisen L.M., Piou D., Vannini A., Interactive effects of drought and pathogens in forest trees, Ann. For. Sci. 63 (2006) 595-610.
  27. Duchemin B., Goubier J., Courrier G., Monitoring phenological key-stages and cycle duration of temperate deciduous forest ecosystems with NOAA-AVHRR data, Remote Sens. Environ. 67 (1999) 68-82 [CrossRef].
  28. Duchemin B., Guyon D., Lagouarde J.P., Potential and limits of NOAA-AVHRR temporal composite data for phenology and water stress monitoring of temperate forest ecosystems, Int. J. Remote Sens. 20 (1999) 895-917 [CrossRef].
  29. Durand P., Gelpe J., Lemoine B., Riom J., Timbal J., Le dépérissement du chêne pédonculé dans les Pyrénées Atlantiques, Rev. For. Fr. (Nancy) 35 (1983) 357-368.
  30. Durrieu S., Deshayes M., Méthode de comparaison d'images satellitaires pour la détection des changements en milieu forestier; application aux Monts de Lacaune (Tarn, France), Ann. For. Sci. 51 (1994) 147-161.
  31. Farcy C., Aerial photography and evaluation of Norway spruce decline in the Ardennes, Ann. For. Sci. 46 (1989) 155-171.
  32. French N.H.F., Bourgeau-Chavez L.L., Initial observations of RADARSAT imagery at fire-disturbed sites in interior Alaska, Remote Sens. Environ. 68 (1999) 89-94 [CrossRef].
  33. Gao B.-C., NDWI - A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space, Remote Sens. Environ. 58 (1996) 257-266 [CrossRef].
  34. Gimeno M., San-Miguel-Ayanz J., Evaluation of RADARSAT-1 data for identification of burnt areas in Southern Europe, Remote Sens. Environ. 92 (2004) 370-375 [CrossRef].
  35. Gimeno M., San-Miguel-Ayanz J., Schmuck G., Identification of burnt areas in Mediterranean forest environments from ERS-2 SAR time series, Int. J. Remote Sens. 25 (2004) 4873-4888 [CrossRef].
  36. Gobron N., Mélin F., Pinty B., Verstraete M.M., Widlowski J.-L., Bucini G., A Global Vegetation Index for SeaWiFS: Design and Applications, in: Beniston M., Verstraete M.M. (Eds.), Satellite Remote Sensing Data and Climate Model Simulations: Synergies and Limitations, Kluwer Academic Publishers, Dordrecht, 2001.
  37. Gobron N., Pinty B., Melin F., Taberner M., Verstraete M.M., Belward A., Lavergne T., Widlowski J.L., The state of vegetation in Europe following the 2003 drought, Int. J. Remote Sens. 26 (2005) 2013-2020 [CrossRef].
  38. Gobron N., Pinty B., Verstraete M.M., Govaerts Y., The MERIS Global Vegetation Index (MGVI): description and preliminary application, Int. J. Remote Sens. 20 (1999) 1917-1927 [CrossRef].
  39. Gu X.F., Seguin B., Hanocq J.F., Guinot J.P., Evaluation and comparison of atmospheric correction methods for thermal data measured by ERS1-ATSR, NOAA11-AVHRR, and Landsat5-TM sensors, in: Proceedings of ISPRS 6th International Symposium Physical Measurements and Signatures in Remote Sensing, Val d'Isère, France, 17-21 Janv. 1994, pp. 793-800.
  40. Guyon D., Riom J., Qualité de l'estimation spatiale d'un phénomène évolutif appréhendé par échantillonnage. Exemple de dépérissement des forêts vosgiennes par photographie aérienne, in: Buche P., King D., Lardon S. (Eds.), Séminaire INRA Gestion de l'espace rural et SIG Florac 22-24 octobre 1991, INRA, 1992, pp. 295-305.
  41. Guyon D., Riom J., Kicin J.L., Letouzé F., Courrier G., Applications de la télédétection et des systèmes d'information géographique à l'étude et la gestion des peuplements forestiers dépérissants. Compte-rendu final, novembre 1997, Projet CEE/DGVI (règlement 3528/86) N° 92.60.fr.0020. 1997, 75 p.
  42. Guyon D., Berbigier P., Courrier G., Lagouarde J.P., Moreau P., Sensitivity analysis of coniferous forest reflectance with canopy structure and undergrowth characteristics from satellite data and modelling (case study: Landes maritime pine forest), in: CNES (Ed.), 8th International Symposium Mesures Physiques et signatures en télédétection, Aussois, 8-12 January 2001, 387-392.
  43. Guyon D., Cardot H., Hagolle O., Monitoring and mapping the phenology of the maritime pine forest of southwestern France from VEGETATION time-series, in: 2nd International Symposium Recent Advances In Quantitative Remote Sensing, Valencia (Spain), September 25th-29th, 2006.
  44. Guyon J.P., Guyon D., Riom J., Causes et gestion du dépérissement du pin maritime sur le littoral Nord-Atlantique. Rev. For. Fr. (Nancy), N° spécial Les dépérissements d'arbres forestiers - causes connues et inconnues, 46 (1994), 485-494.
  45. Hagolle O., Lobo A., Maisongrande P., Cabot F., Duchemin B., De Pereyra A., Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 & 2 images, Remote Sens. Environ. 94 (2005) 172-186 [CrossRef].
  46. Haara A., Nevalainen S., Detection of dead or defoliated spruces using digital aerial data, For. Ecol. Manage. 160 (2002) 97-107 [CrossRef].
  47. Harrell P.A., Bourgeau-Chavez L.L., Kasischke E.S., French N.H.F., Christensen N.L. Jr., Sensitivity of ERS-1 and JERS-1 Radar Data to Biomass and Stand Structure in Alaskan Boreal Forest, Remote Sens. Environ. 54 (1995) 247-260 [CrossRef].
  48. Haussmann T., Lorenz M., Fisher R., Internal Review of ICP Forests, 16th Task Force Meeting of ICP Forests (Gent, Belgium), May 2000, UN/ECE Report, 133 p.
  49. Hildebrandt G., Pilotinventur für eine Europaïsche Wald schadensinventür, in: Proceed. IUFRO Conference, 402/605, Inventoring and Monitoring Endangered Forests, Zürich, 1985, pp. 237-242.
  50. Holmgren P., Thuresson T., Satellite remote sensing for forestry planning - A review, Scand. J. For. Res. 13 (1998) 90-110.
  51. Hunt E.R. Jr., Rock B.N., Detection of changes in leaf water content using near- and middle-infrared reflectances, Remote Sens. Environ. 30 (1989) 43-54 [CrossRef].
  52. Jeanjean H., Deshayes M., Synthèse Zones forestières et SPOT4 MIR, in: SPOT4 MIR Synthèse thématique, Centre National d'Études Spatiales, Paris, France, 1998.
  53. Ji L., Peters A.J., Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices, Remote Sens. Environ. 87 (2003) 85-98 [CrossRef].
  54. Jolly A., Estimation par télédétection satellitaire de la récolte annuelle en bois dans la futaie pure de pin maritime du massif des Landes de Gascogne, Apports pour la prévision de la ressource forestière, Thèse de doctorat de l'Université Paul Sabatier de Toulouse, Spécialité: Télédétection spatiale (N° 1626), 17 décembre 1993, 315 p.
  55. Jolly A., Guyon D., Riom J., Use of Landsat Thematic Mapper middle infrared data to detect clearcuts in the Landes region, Int. J. Remote Sens. 17 (1996) 3615-3645.
  56. Joria P., Ahearn S., Connor M., A comparison of the SPOT and Landsat Thematic Mapper satellite systems for detecting gypsy moth defoliation in Michigan, Photogramm. Eng. Remote Sens. 57 (1991) 1605-1612.
  57. Kasischke E.S., Bourgeau-Chavez L.L., French N.F., Observations of variations in ERS-1 SAR image intensity associated with forest fires in Alaska, IEEE Trans. Geosci. Remote Sens. 32 (1994) 206-210.
  58. Kasischke E.S., Melack J.M., Dobson M.C., The Use of Imaging Radars for Ecological Applications - A Review, Remote Sens. Environ. 59 (1997) 141-156 [CrossRef].
  59. Kerr Y.H., Lagouarde J.P., Imbernon J., Accurate land surface temperature retrieval from AVHRR data with use of an improved split-window algorithm, Remote Sens. Environ. 41 (1992) 197-209 [CrossRef].
  60. Kimes B.L., Markham B.L., Tucker C.J., McMurtrey J.E., Temporal Relationships Between Spectral Response and Agronomic Variables of a Corn Canopy, Remote Sens. Environ. 11 (1981) 401-412 [CrossRef].
  61. Kogan F.N., Drought of the late 1980s in the US as derived from NOAA polar orbiting satellite data, Bull. Am. Meteorol. Soc. 76 (1995) 655-667 [CrossRef].
  62. Kuntz S., Siegert F., Monitoring of deforestation and land use in Indonesia with multitemporal ERS data, Int. J. Remote Sens. 20 (1999) 2835-2853 [CrossRef].
  63. Lagouarde J.-P., Ballans F., Moreau P., Guyon D., Coraboeuf D., Experimental study of brightness surface angular variations of maritime pine (Pinus pinaster) stands, Remote Sens. Environ. 72 (2000) 17-34 [CrossRef].
  64. Leckie D.G., Jay C., Paradine D., Sturrock R., Preliminary assessment of Phellinus weirii infected (laminated root rot) trees with high resolution CASI imagery, in: Hill D.A., Leckie D.G. (Eds.), Proceedings Automated Interpretation of High Spatial Resolution Digital Imagery For Forestry, International Forum, Victoria, British Columbia, February 10-12, 1998, Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia, 1999, pp. 187-195.
  65. Levesque J., King D.J., Airborne digital camera image semivariance for evaluation of forest structural damage at an acid mine site, Remote Sens. Environ. 68 (1999) 112-124 [CrossRef].
  66. Liu W.T., Kogan F.N., Monitoring regional drought using the Vegetation Condition, Int. J. Remote Sens. 17 (1996) 2761-2782.
  67. Lobo A., Maisongrande P., Stratified analysis of satellite imagery of SW Europe during summer 2003: the differential response of vegetation classes to increased water deficit, Hydrol. Earth Syst. Sci. Discuss. 2 (2005) 2025-2060.
  68. López S., González F., Llop R., Cuevas M., An evaluation of the utility of NOAA-AVHRR images for monitoring forest fire risk in Spain, Int. J. Remote Sens. 12 (1991) 1841-1851.
  69. Luckman A., Baker J., Honzak M., Lucas R., Tropical forest biomass density estimation using JERS-1 SAR: Seasonal variation, confidence limits, and application to image mosaics - active and passive, Remote Sens. Environ. 63 (1997) 126-139 [CrossRef].
  70. Mårell A., Leitgeb E., European long-term research for sustainable forestry: experimental and monitoring assets at the ecosystem and landscape level. Part 1: country reports, Technical Report 3, COST Action E25, ECOFOR, Paris, 2005.
  71. Maselli F., Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data, Remote Sens. Environ. 89 (2004) 423-433 [CrossRef].
  72. Melia J., Lopez-Baeza E., Caselles V., Segarra D., Sobrino J.A., Gilabert M.A., Moreno J., Coll C. EFEDA Annual Report, EPOC-CT90-0030 (LNBE), University of Valencia, 1991.
  73. Miller D.R., Quine C.P., Hadley W., An investigation of the potential of digital photogrammetry to provide measurements of forest characteristics and abiotic damage, For. Ecol. Manage. 135 (2000) 279-288 [CrossRef].
  74. Myneni R.B., Keeling C.D., Tucker C.J., Asrar G., Nemani R.R., Increased plant growth in the Northern high latitudes from 1981-1991, Nature, 386 (1997) 698-702.
  75. Ogée J., Brunet Y., Loustau D., Berbigier P., Delzon S., MuSICA, a CO2, water and energy multi-layer, multi-leaf pine forest model: evaluation from hourly to yearly time scales and sensitivity analysis, Glob. Change Biol. 9 (2003) 697-717 [CrossRef].
  76. Pereira J.M.C., Govaerts Y., Potential Fire Applications from MSG/SEVIRI Observations. EUMETSAT Programme Development Department Technical Memorandum No. 07, 2001.
  77. Ranson K.J., Kovacs K., Sun G., Kharuk V.I., Disturbance recognition in the boreal forest using radar and Landsat-7, Can. J. Remote Sens. 29 (2003) 271-285.
  78. Rederstorff D., Dépérissement forestier en Vallée du Rhin - Waldschäden im Rheintal. Photointerprétation du dépérissement. Mission aérienne du 9 août 1994, Office National des Forêts - Observatoire écologique de la Harth, Strasbourg, Forstlische Versuch- und Forschunsanstalt Baden-Württemberg, Freiburg-im-Breisgau, 1996.
  79. Reichle R.H., Koster R.D., Dong J., Berg A.A., Global soil moisture from satellite observations, lands surface models and ground data: implications for data assimilation, J. Hydrometeo. 5 (2004) 430-442.
  80. Rigina O., Baklanov A., Hagner O., Olsson H., Monitoring of forest damage in the Kola Peninsula, Northern Russia due to smelting industry, Sci. Total Environ. 229 (1999) 147-163 [CrossRef].
  81. Rignot E., Salas W.A., Skole D.L., Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data, Remote Sens. Environ. 59 (1997) 167-179 [CrossRef].
  82. Riom J., Le dépérissement du Chêne - Apports de la Télédétection. 1. Forêts des Pyrénées Atlantiques. 2. Forêt du Tronçais (Allier), in: Les Colloques de l'INRA, N° 32 : Applications de la Télédétection à l'Agriculture, INRA, Paris, 1984, pp. 117-145.
  83. Riom J., Apport de la télédétection pour l'estimation des dommages aux forêts vosgiennes, Colloque DEFORPA, Nancy, 24-26 février 1988, 32 p.
  84. Riom J., Reteau F., Guyon D., Démonstration de l'application de la télédétection par méthode photographique pour l'estimation des dégâts aux forêts. Essai sur le massif forestier vosgien, C.R. de fin de contrat CEE DG VI, APPF/II 5B (VIP F3/81) code INRA 4100A, juin 1987, 120 p.
  85. Ripple W.J., Spectral reflectance relationships to leaf water stress, Photogramm, Eng. Remote Sens. 52 (1986) 1669-1775.
  86. Rouse J.W., Haas R.H., Schell J.A., Deering D.W., Monitoring vegetation systems in the Great Plains with ERTS, in: Freden S.C., Becker M. (Eds.), Third earth resources technology satellite-1 symposium, NASA SP-351, Washington, DC, 1974, Vol. 1, pp. 309-317.
  87. Saich P., Rees W.G., Borgeaud M., Detecting pollution damage to forests in the Kola peninsula using the ERS SAR, Remote Sens. Environ. 75 (2001) 22-28 [CrossRef].
  88. Schwarz M., Steinmeier C., Holecz F., Stebler O., Wagner H., Detection of windthrow in mountainous regions with different remote sensing data and classification methods, Scand. J. For. Res. 18 (2003) 525-536 [CrossRef].
  89. Seguin B., Becker F., Phulpin T., Gu X.F., Guyot G., Kerr Y., King C., Lagouarde J.P., Ottlé C., Stoll P.M., Tabbagh A., Vidal A., A mini satellite project for land surface heat flux estimation from field to regional scale, Remote Sens. Environ. 68 (1999) 357-369 [CrossRef].
  90. Siegert F., Kuntz S., Streck C., Bergbauer B., Land use planning and monitoring in Indonesia using ERS-1 RADAR data, in: Proceedings International Conference on Remote Sensing and GIS for Environmental Resources Management - The Indonesian-European Experience, Jakarta, Indonesia, 6-8 June 1995.
  91. Skakun R.S., Wulder M.A., Franklin S.E., Sensitivity of the Thematic Mapper enhanced wetness difference index to detect mountain pine beetle red-attack damage, Remote Sens. Environ. 86 (2003) 433-443 [CrossRef].
  92. Stach N., L'IFN cartographie les dégâts de la tempête sur le massif aquitain de pin maritime, Géomatique Expert 5 (2000) 15-17.
  93. Stach N., Deshayes M., Durrieu S., Mapping clear-cutting in French forests by satellite remote sensing, in: Olsson H. (Ed.), Proceedings of ForestSat 2005, Borås May 31-June 3 2005, Swedish National Board of Forestry 8a (2005) 118-125.
  94. Stach N., Deshayes M., Le Toan T., Mapping storm damage to forests using optical and radar remote sensing - The case of the December 1999 storms in France, in: Olsson H. (Ed.), Proceedings of ForestSat 2005, Borås May 31-June 3 2005, Swedish National Board of Forestry 8a (2005) 89-93.
  95. Stach N., Deshayes M., Le Toan T., Campillo D., Mathieu G., Évaluation des dégâts de tempête par télédétection satellitaire : aspects méthodologiques et opérationnels, Rapport final, Convention DERF N° 2001-12-132, 2002, 148 p., 2 annexes.
  96. Stone C., Coops N.C., Assessment and monitoring of damage from insects in Australian eucalypt forests and commercial plantations, Aust. J. Entomol. 43 (2004) 283-292 [CrossRef].
  97. Tommervik H., Hogda K.A., Solheim L., Monitoring vegetation changes in Pasvik (Norway) and Pechenga in Kola Peninsula (Russia) using multitemporal Landsat MSS/TM data, Remote Sens. Environ. 85 (2003) 370-388 [CrossRef].
  98. Tucker C.J., Sellers P.J., Satellite remote sensing of primary production, Int. J. Rem. Sens. 7 (1986) 1395-1416.
  99. Valette J.C., Inflammabilité des espèces forestières méditerranéennes. Conséquences sur la combustibilité des formations forestières, Rev. For. Fr. (Nancy) 42 (1990) 76-92.
  100. Vidal A., Atmospheric and emissivity corrections of land surface temperature measured from satellite using ground measurements or satellite data, Int. J. Rem. Sens. 12 (1991) 2449-2460.
  101. Vidal A., Pinglo F., Durand H., Devaux-Ros C., Maillet A., Evaluation of a temporal fire risk index in Mediterranean forests from NOAA thermal IR, Remote Sens. Environ. 49 (1994) 296-302 [CrossRef].
  102. Wang Quan, Tenhunen J., Dinh NguyenQuoc, Reichstein M., Vesala T., Keronen P., Similarities in ground- and satellite-based NDVI time series and their relationship to physiological activity of a Scots pine forest in Finland, Remote Sens. Environ. 93 (2004) 225-237 [CrossRef].
  103. Wang Quan, Adiku S., Tenhunen J., Granier A., On the relationship of NDVI with leaf area index in a deciduous forest site, Remote Sens. Environ. 94 (2005) 244-255 [CrossRef].
  104. Wigneron J.P., Calvet J.C., Pellarin T., Van De Griend A., Berger M., Chanzy A., Ferrazzoli P., Retrieving near surface soil moisture from microwave radiometric observations: current status and future plans, Remote Sens. Environ. 85 (2003) 489-506 [CrossRef].
  105. Yanasse C.d.C.F., Sant'Anna S.J.S., Frery A.C., Renno C.D., Soares J.V., Luckman A.J., Exploratory study of the relationship between tropical forest regeneration stages and SIR-C L and C data, Remote Sens. Environ. 59 (1997) 180-190 [CrossRef].
  106. Yu G.R., Miwa T., Nakayama K., Matsuoka N., Kon H., A proposal for universal formulas for estimating leaf water status of herbaceous and woody plants based on spectral reflectance properties, Plant Soil 227 (2000) 47-58 [CrossRef].
  107. Zarco-Tejada P.J., Miller J.R., Harron J., Hu B., Noland T.L., Goel N., Sampson P.H., Mohammed G.H., Hyperspectral remote sensing of forest condition: estimating chlorophyll content in tolerant hardwoods, For. Sci. 49 (2003) 381-391.
  108. Zhang P., Anderson B., Barlow M., Tan B., Myneni R.B., Climate-related vegetation characteristics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index and normalized difference vegetation index, J. Geophys. Res. Atmos. 109 (2004).
  109. Zhang X.Y., Friedl M.A., Schaaf C.B., Strahler A.H., Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data, Glob. Change Biol. 10 (2004) 1133-1145 [CrossRef].